Capacity Expansion

Capacity expansion planning aims to optimize the allocation of resources to meet future demands under uncertainty, minimizing costs while ensuring sufficient capacity. Recent research focuses on improving the efficiency and robustness of existing optimization models, employing techniques like Bayesian optimization, adversarial generative learning, and graph convolutional autoencoders to handle high-dimensional uncertainty and large-scale problems. These advancements are particularly relevant for sectors like energy and healthcare, enabling more cost-effective decarbonization strategies and improved resource allocation in medical residency programs, for example. The ultimate goal is to develop more tractable and accurate models that lead to better decision-making in complex systems.

Papers

September 5, 2024

A Deep Generative Learning Approach for Two-stage Adaptive Robust Optimization
Aron Brenner, Rahman Khorramfar, Jennifer Sun, Saurabh Amin
Native Robustness Robust Optimization Contingency Game Generative Deep Learning Approach Capacity Expansion

January 19, 2024

Learning-assisted Stochastic Capacity Expansion Planning: A Bayesian Optimization Approach
Aron Brenner, Rahman Khorramfar, Dharik Mallapragada, Saurabh Amin
Bayesian Optimization Stochastic Optimization Renewable Energy Capacity Expansion

March 16, 2023

Learning Spatio-Temporal Aggregations for Large-Scale Capacity Expansion Problems
Aron Brenner, Rahman Khorramfar, Saurabh Amin
Renewable Energy Spatial Global Local Aggregation Spatio Temporal Aggregation Capacity Expansion

February 14, 2022

Anytime Capacity Expansion in Medical Residency Match by Monte Carlo Tree Search
Kenshi Abe, Junpei Komiyama, Atsushi Iwasaki
Monte Carlo Tree Search Mixed Integer Medical Text Capacity Gap Optimal Assignment Capacity Expansion

Capacity Expansion

Papers

A Deep Generative Learning Approach for Two-stage Adaptive Robust Optimization

Learning-assisted Stochastic Capacity Expansion Planning: A Bayesian Optimization Approach

Learning Spatio-Temporal Aggregations for Large-Scale Capacity Expansion Problems

Anytime Capacity Expansion in Medical Residency Match by Monte Carlo Tree Search